Week7, 2021

### Libraries ###
library(tidyverse)
library(tidytuesdayR)
library(here)
library(plotly)
library(scales)
library(htmlwidgets)

rm(list=ls())

### Bring in Data ###
tuesdata <- tt_load(2021, week = 7)

## 
##  Downloading file 1 of 11: `home_owner.csv`
##  Downloading file 2 of 11: `income_aggregate.csv`
##  Downloading file 3 of 11: `income_distribution.csv`
##  Downloading file 4 of 11: `income_limits.csv`
##  Downloading file 5 of 11: `income_mean.csv`
##  Downloading file 6 of 11: `income_time.csv`
##  Downloading file 7 of 11: `lifetime_earn.csv`
##  Downloading file 8 of 11: `lifetime_wealth.csv`
##  Downloading file 9 of 11: `race_wealth.csv`
##  Downloading file 10 of 11: `retirement.csv`
##  Downloading file 11 of 11: `student_debt.csv`

race_wealth <- tuesdata$race_wealth


### Data Analysis ###
glimpse(race_wealth)

## Rows: 96
## Columns: 4
## $ type          <chr> "Average", "Average", "Average", "Average", "Average", "…
## $ year          <dbl> 1963, 1963, 1963, 1963, 1983, 1983, 1983, 1983, 1989, 19…
## $ race          <chr> "Non-White", "White", "Black", "Hispanic", "Non-White", …
## $ wealth_family <dbl> 19503.84, 140632.66, NA, NA, 73233.62, 324057.60, 67269.…

static<-race_wealth %>% 
  ggplot(aes(x=year, y=wealth_family,
             color=race, fill=race)) +
  geom_bar(stat="identity", position="dodge", aes(color = race)) + 
  labs(color="Race", fill = "Race",
       x="Year", y="Average Family Wealth per Year") + 
  theme_bw()


race_wealth %>% 
  plot_ly(x=~year, y=~wealth_family,
          color=~race, fill=~race,
          type = "bar",
          text = ~paste0("Annual Family Income: $", # customize hover label text
                        comma(round(wealth_family),decimals = 2)),
          hovertemplate = paste('%{text}')) %>% 
  layout(title = "Annual Family Income", #change plot title
         xaxis = list(title = "Year"), #change x-axis title
         yaxis = list(title = "Annual Income (USD)")) #change y-axis title